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Compressed Sensing and tutorial June 7, 2010

Posted by Sarah in Uncategorized.
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I’m going to be going to the Park City Math Institute’s summer program at the end of June. The topic is Image Processing and there are lecture courses on mathematical image processing and compressed sensing, as well as whatever graduate lectures I also have time for. I’m excited about the whole thing.

So, in preparation, have been reading about compressed sensing, and the nicest and most complete tutorial I could find is this one by Richard Baraniuk: (PDF here). Compressed sensing, in short, is how you beat the Shannon bound; you can collect very few measurements and nonetheless reconstruct the signal perfectly. This, to drastically understate the point, is useful. Now I’m tempted to do nothing but read papers. (However, there’s also Serious Business to be done — currently Stein’s Singular Integrals.)

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1. Igor Carron - June 8, 2010

Stein’s Singular Integrals might be Serious Business, but Compressive Sensing is Important Business 🙂

Cheers,

Igor.


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